--- title: "FasterTransformer vs faster-whisper" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nvidia-fastertransformer-vs-systran-faster-whisper" tools: ["nvidia-fastertransformer", "systran-faster-whisper"] --- # FasterTransformer vs faster-whisper *GraphCanon updated Aug 7, 2026* ## Verdict Pick FasterTransformer if highly optimized transformer encoder and decoder for inferencing, supporting BERT and GPT on various frameworks like TensorFlow, PyTorch; pick faster-whisper if a package for faster speech-to-text transcription based on the Whisper model, using CTranslate2. [FasterTransformer](https://github.com/NVIDIA/FasterTransformer) reports 6.4k GitHub stars, 935 forks, and 289 open issues, last pushed Mar 27, 2024. [faster-whisper](https://github.com/SYSTRAN/faster-whisper) has 25k stars, 2.0k forks, and 315 open issues, last pushed Nov 19, 2025. Figures are from public GitHub metadata via [FasterTransformer's repository](https://github.com/NVIDIA/FasterTransformer) and [faster-whisper's repository](https://github.com/SYSTRAN/faster-whisper). | | [FasterTransformer](/tools/nvidia-fastertransformer.md) | [faster-whisper](/tools/systran-faster-whisper.md) | | --- | --- | --- | | Tagline | Transformer related optimization including BERT and GPT | Faster Whisper transcription with CTranslate2 | | Stars | 6,446 | 24,689 | | Forks | 935 | 2,006 | | Open issues | 289 | 315 | | Language | C++ | Python | | Adopt for | Highly optimized transformer encoder and decoder for inferencing, supporting BERT and GPT on various frameworks like TensorFlow, PyTorch. | A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Inference & Serving | Inference & Serving, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [FasterTransformer](/tools/nvidia-fastertransformer.md) | [faster-whisper](/tools/systran-faster-whisper.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 862d | 255d | | Open issues (now) | 289 | 315 | | Full report | [trust report](/tools/nvidia-fastertransformer/trust.md) | [trust report](/tools/systran-faster-whisper/trust.md) | ## Decision facts: FasterTransformer - **Adopt for:** Highly optimized transformer encoder and decoder for inferencing, supporting BERT and GPT on various frameworks like TensorFlow, PyTorch. ## Decision facts: faster-whisper - **Requirements:** Requires Python 3.9 or higher - **Adopt for:** A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2. ## Choose when ### Choose FasterTransformer if… - FasterTransformer is primarily C++; faster-whisper is Python. - License: FasterTransformer is Apache-2.0, faster-whisper is MIT. - Tags unique to FasterTransformer: bert, cublas, cublaslt, cuda. - When aiming for high performance with GPU-based FP16 computations for BERT or GPT models specifically. ### Choose faster-whisper if… - faster-whisper is primarily Python; FasterTransformer is C++. - License: faster-whisper is MIT, FasterTransformer is Apache-2.0. - Requirements: Requires Python 3.9 or higher. - Tags unique to faster-whisper: deep-learning, inference, openai, quantization. - Also covers Speech & Audio. - A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2. ## When NOT to use FasterTransformer - If looking for active development and latest improvements on LLM Inference as NVIDIA recommends TensorRT-LLM over FasterTransformer now. - When specific frameworks not including TensorFlow, PyTorch, or Triton are required. ## When NOT to use faster-whisper - * When needing to employ FFmpeg directly for audio processing as it does not require FFmpeg installation and relies instead on PyAV. - * In environments where additional dependencies from PyAV may introduce complexity or issues. ## Common questions ### What is the difference between FasterTransformer and faster-whisper? FasterTransformer: Transformer related optimization including BERT and GPT. faster-whisper: Faster Whisper transcription with CTranslate2. See the comparison table for live GitHub stats and shared categories. ### When should I choose FasterTransformer over faster-whisper? Choose FasterTransformer over faster-whisper when FasterTransformer is primarily C++; faster-whisper is Python; License: FasterTransformer is Apache-2.0, faster-whisper is MIT; Tags unique to FasterTransformer: bert, cublas, cublaslt, cuda; When aiming for high performance with GPU-based FP16 computations for BERT or GPT models specifically. ### When should I choose faster-whisper over FasterTransformer? Choose faster-whisper over FasterTransformer when faster-whisper is primarily Python; FasterTransformer is C++; License: faster-whisper is MIT, FasterTransformer is Apache-2.0; Requirements: Requires Python 3.9 or higher; Tags unique to faster-whisper: deep-learning, inference, openai, quantization; Also covers Speech & Audio; A package for faster speech-to-text transcription based on the Whisper model, using CTranslate2. ### When should I avoid FasterTransformer? If looking for active development and latest improvements on LLM Inference as NVIDIA recommends TensorRT-LLM over FasterTransformer now. When specific frameworks not including TensorFlow, PyTorch, or Triton are required. ### When should I avoid faster-whisper? * When needing to employ FFmpeg directly for audio processing as it does not require FFmpeg installation and relies instead on PyAV. * In environments where additional dependencies from PyAV may introduce complexity or issues. ### Is FasterTransformer or faster-whisper more popular on GitHub? faster-whisper has more GitHub stars (24,689 vs 6,446). Stars measure visibility, not whether either tool fits your constraints. ### Are FasterTransformer and faster-whisper open source? Yes - both are open-source projects on GitHub (FasterTransformer: Apache-2.0, faster-whisper: MIT). ### Where can I find alternatives to FasterTransformer or faster-whisper? GraphCanon lists graph-backed alternatives at [FasterTransformer alternatives](/tools/nvidia-fastertransformer/alternatives) and [faster-whisper alternatives](/tools/systran-faster-whisper/alternatives) ([FasterTransformer markdown twin](/tools/nvidia-fastertransformer/alternatives.md), [faster-whisper markdown twin](/tools/systran-faster-whisper/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/nvidia-fastertransformer-vs-systran-faster-whisper.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, FasterTransformer or faster-whisper? FasterTransformer: Dormant. faster-whisper: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for FasterTransformer and faster-whisper? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [FasterTransformer trust report](/tools/nvidia-fastertransformer/trust); [faster-whisper trust report](/tools/systran-faster-whisper/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nvidia-fastertransformer`](/api/graphcanon/graph?tool=nvidia-fastertransformer) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_